Countrywise Plots
Plot – Vaccines per day | Percentage of vaccined population | Daily Vaccinations
Argentina - AR
argentina <- vaccinations[grep("ARG", vaccinations$iso_code),]
argentina_world_pop <- world_population[grep("Argentina", world_population$Country),]
argentina$population = argentina_world_pop$Population
argentina$percentage = (argentina$people_vaccinated/argentina$population)*100
plot_argentina <- argentina %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇦🇷") +
scale_y_continuous(breaks = seq(0, 100000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_argentina_1 = plot_argentina
plot_argentina_1 = plot_argentina_1 + ggtitle("Population Vaccinated on \n Argentina (2021)") +
theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_argentina_percentage <- argentina %>%
ggplot( aes(x=date, y=percentage, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇦🇷") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_argentina_2 = plot_argentina_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_argentina_2 = plot_argentina_2 + ggtitle("Population (%) Vaccinated \n on Argentina") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_argentina_daily_vac <- argentina %>%
ggplot( aes(x=date, y=daily_vaccinations)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇦🇷") +
scale_y_continuous(breaks = seq(0, 100000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_argentina_interactive <- plot_ly(x = argentina$date, y = argentina$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_argentina_interactive2 <- plot_ly(x = argentina$date, y = argentina$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_argentina_interactive3 <- plot_ly(x = argentina$date, y = argentina$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_argentina_interactive,plot_argentina_interactive2,plot_argentina_interactive3, nrows=1 , margin= 0.05)
Austria - AT
austria <- vaccinations[grep("AUT", vaccinations$iso_code),]
austria_world_pop <- world_population[grep("Austria", world_population$Country),]
austria$population = austria_world_pop$Population
austria$percentage = (austria$people_vaccinated/austria$population)*100
plot_austria <- austria %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇦🇹") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_austria_1 = plot_austria+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_austria_1 = plot_austria_1 + ggtitle("Population Vaccinated on \n Austria (2021)")
plot_austria_percentage <- austria %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇦🇹") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_austria_2 = plot_austria_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_austria_2 = plot_austria_2 + ggtitle("Population (%) Vaccinated \n on Austria") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_austria_interactive <- plot_ly(x = austria$date, y = austria$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_austria_interactive2 <- plot_ly(x = austria$date, y = austria$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_austria_interactive3 <- plot_ly(x = austria$date, y = austria$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_austria_interactive,plot_austria_interactive2,plot_austria_interactive3, nrows=1 , margin= 0.05)
Bahrain - BH
bahrain <- vaccinations[grep("BHR", vaccinations$iso_code),]
bahrain_world_pop <- world_population[grep("Bahrain", world_population$Country),]
bahrain$population = bahrain_world_pop$Population
bahrain$percentage = (bahrain$people_vaccinated/bahrain$population)*100
bahrain$percentage[is.na(bahrain$percentage)] <- round(mean(bahrain$percentage, na.rm = TRUE))
plot_bahrain <- bahrain %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇧ðŸ‡") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_bahrain_1 = plot_bahrain+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_bahrain_1 = plot_bahrain_1 + ggtitle("Population (%) \n Vaccinated on \n Bahrain (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_bahrain_percentage <- bahrain %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇧ðŸ‡") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_bahrain_2 = plot_bahrain_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_bahrain_2 = plot_bahrain_2 + ggtitle("Population Vaccinated \n on Bahrain") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_bahrain_interactive <- plot_ly(x = bahrain$date, y = bahrain$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_bahrain_interactive2 <- plot_ly(x = bahrain$date, y = bahrain$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_bahrain_interactive3 <- plot_ly(x = bahrain$date, y = bahrain$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_bahrain_interactive,plot_bahrain_interactive2,plot_bahrain_interactive3, nrows=1 , margin = 0.05)
Belgium - BE
belgium <- vaccinations[grep("BEL", vaccinations$iso_code),]
belgium_world_pop <- world_population[grep("Belgium", world_population$Country),]
belgium$population = belgium_world_pop$Population
belgium$percentage = (belgium$people_vaccinated/belgium$population)*100
plot_belgium <- belgium %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇧🇪") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_belgium_1 = plot_belgium+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_belgium_1 = plot_belgium_1 + ggtitle("Population (%) \n Vaccinated on \n Belgium (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_belgium_percentage <- belgium %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇧🇪") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_belgium_2 = plot_belgium_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_belgium_2 = plot_belgium_2 + ggtitle("Population (%) Vaccinated \n on Belgium") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_belgium_interactive <- plot_ly(x = belgium$date, y = belgium$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_belgium_interactive2 <- plot_ly(x = belgium$date, y = belgium$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_belgium_interactive3 <- plot_ly(x = belgium$date, y = belgium$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_belgium_interactive,plot_belgium_interactive2,plot_belgium_interactive3, nrows=1 , margin = 0.05)
Brazil - BR
brazil <- vaccinations[grep("BRA", vaccinations$iso_code),]
brazil_world_pop <- world_population[grep("Brazil", world_population$Country),]
brazil$population = brazil_world_pop$Population
brazil$percentage = (brazil$people_vaccinated/brazil$population)*100
plot_brazil <- brazil %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇧🇷") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_brazil_1 = plot_brazil+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_brazil_1 = plot_brazil_1 + ggtitle("Population (%) \n Vaccinated on \n Brazil (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_brazil_percentage <- brazil %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇧🇷") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_brazil_2 = plot_brazil_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_brazil_2 = plot_brazil_2 + ggtitle("Population (%) Vaccinated \n on Brazil") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_brazil_interactive <- plot_ly(x = brazil$date, y = brazil$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_brazil_interactive2 <- plot_ly(x = brazil$date, y = brazil$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_brazil_interactive3 <- plot_ly(x = brazil$date, y = brazil$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_brazil_interactive,plot_brazil_interactive2,plot_brazil_interactive3, nrows=1 , margin = 0.05)
Bulgaria - BG
bulgaria <- vaccinations[grep("BGR", vaccinations$iso_code),]
bulgaria_world_pop <- world_population[grep("Bulgaria", world_population$Country),]
bulgaria$population = bulgaria_world_pop$Population
bulgaria$percentage = (bulgaria$people_vaccinated/bulgaria$population)*100
plot_bulgaria <- bulgaria %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇧🇬") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_bulgaria_1 = plot_bulgaria+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_bulgaria_1 = plot_bulgaria_1 + ggtitle("Population Vaccinated on \n Bulgaria (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_bulgaria_percentage <- bulgaria %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇧🇬") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_bulgaria_2 = plot_bulgaria_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_bulgaria_2 = plot_bulgaria_2 + ggtitle("Population (%) Vaccinated \n on Bulgaria") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_bulgaria_interactive <- plot_ly(x = bulgaria$date, y = bulgaria$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_bulgaria_interactive2 <- plot_ly(x = bulgaria$date, y = bulgaria$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_bulgaria_interactive3 <- plot_ly(x = bulgaria$date, y = bulgaria$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_bulgaria_interactive,plot_bulgaria_interactive2,plot_bulgaria_interactive3, nrows=1 , margin=0.05)
Canada - CA
canada <- vaccinations[grep("CAN", vaccinations$iso_code),]
canada_world_pop <- world_population[grep("Canada", world_population$Country),]
canada$population = canada_world_pop$Population
canada$percentage = (canada$people_vaccinated/canada$population)*100
plot_canada <- canada %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇨🇦") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_canada_1 = plot_canada+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_canada_1 = plot_canada_1 + ggtitle("Population (%) Vaccinated on Canada (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_canada_percentage <- canada %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇨🇦") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_canada_2 = plot_canada_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_canada_1 = plot_canada_1 + ggtitle("Population Vaccinated \n on Canada") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_canada_interactive <- plot_ly(x = canada$date, y = canada$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_canada_interactive2 <- plot_ly(x = canada$date, y = canada$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_canada_interactive3 <- plot_ly(x = canada$date, y = canada$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_canada_interactive,plot_canada_interactive2,plot_canada_interactive3 ,nrows=1 , margin = 0.05)
Chile - CL
chile <- vaccinations[grep("CHL", vaccinations$iso_code),]
chile_world_pop <- world_population[grep("Chile", world_population$Country),]
chile$population = chile_world_pop$Population
chile$percentage = (chile$people_vaccinated/chile$population)*100
plot_chile<- chile %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇨🇱") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_chile_1 = plot_chile+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_chile_1 = plot_chile_1 + ggtitle("Population Vaccinated on Chile (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_chile_percentage <- chile %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇨🇱") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_chile_2 = plot_chile_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_chile_2 = plot_chile_2 + ggtitle("Population Vaccinated(%) \n on Chile") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_chile_interactive <- plot_ly(x = chile$date, y = chile$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_chile_interactive2 <- plot_ly(x = chile$date, y = chile$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_chile_interactive3 <- plot_ly(x = chile$date, y = chile$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_chile_interactive,plot_chile_interactive2,plot_chile_interactive3, nrows=1 , margin = 0.05)
China - CN
china <- vaccinations[grep("CHN", vaccinations$iso_code),]
china_world_pop <- world_population[grep("China", world_population$Country),]
china$population = china_world_pop$Population
china$percentage = (china$people_vaccinated/china$population)*100
plot_china <- china %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇨🇳") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_china_1 = plot_china+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_china_1 = plot_china_1 + ggtitle("Population Vaccinated on China (2020/21)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_china_percentage <- china %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇨🇳") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_china_2 = plot_china_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_china_2 = plot_china_2 + ggtitle("Population (%) Vaccinated \n on China") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_china_interactive <- plot_ly(x = china$date, y = china$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_china_interactive2 <- plot_ly(x = china$date, y = china$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_china_interactive3 <- plot_ly(x = china$date, y = china$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_china_interactive,plot_china_interactive2,plot_china_interactive3, nrows=1 , margin = 0.05)
Costa Rica - CR
costa_rica <- vaccinations[grep("CRI", vaccinations$iso_code),]
costa_rica_world_pop <- world_population[grep("Costa Rica", world_population$Country),]
costa_rica$population = costa_rica_world_pop$Population
costa_rica$percentage = (costa_rica$people_vaccinated/costa_rica$population)*100
plot_costa_rica <- costa_rica %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇨🇷") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_costa_rica_1 = plot_costa_rica+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_costa_rica_1 = plot_costa_rica_1 + ggtitle("Population (%) Vaccinated \n on Costa Rica") +
theme(plot.title = element_text(size = 6, face = "bold"))
plot_costa_rica_percentage <- costa_rica %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇨🇷") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_costa_rica_2 = plot_costa_rica_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_costa_rica_2 = plot_costa_rica_2 + ggtitle("Population (%) Vaccinated \non Costa Rica") +
theme(plot.title = element_text(size = 6, face = "bold"))
plot_costa_rica_interactive <- plot_ly(x = costa_rica$date, y = costa_rica$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_costa_rica_interactive2 <- plot_ly(x = costa_rica$date, y = costa_rica$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_costa_rica_interactive3 <- plot_ly(x = costa_rica$date, y = costa_rica$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_costa_rica_interactive,plot_costa_rica_interactive2,plot_costa_rica_interactive3, nrows=1 ,margin = 0.05)
Croatia - HR
croatia <- vaccinations[grep("HRV", vaccinations$iso_code),]
croatia_world_pop <- world_population[grep("Croatia", world_population$Country),]
croatia$population = croatia_world_pop$Population
croatia$percentage = (croatia$people_vaccinated/croatia$population)*100
plot_croatia <- croatia %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("ðŸ‡ðŸ‡·") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_croatia_1 = plot_croatia+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_croatia_1 = plot_croatia_1 + ggtitle("Population Vaccinated \n on Croatia (2021)") +
theme(plot.title = element_text(size = 6, face = "bold"))
plot_croatia_percentage <- croatia %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("ðŸ‡ðŸ‡·") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_croatia_2 = plot_croatia_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_croatia_2 = plot_croatia_2 + ggtitle("Population (%) Vaccinated on Croatia") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_croatia_interactive <- plot_ly(x = croatia$date, y = croatia$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_croatia_interactive2 <- plot_ly(x = croatia$date, y = croatia$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_croatia_interactive3 <- plot_ly(x = croatia$date, y = croatia$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_croatia_interactive,plot_croatia_interactive2,plot_croatia_interactive3, nrows=1)
Cyprus - CY
cyprus <- vaccinations[grep("CYP", vaccinations$iso_code),]
cyprus_world_pop <- world_population[grep("Cyprus", world_population$Country),]
cyprus$population = cyprus_world_pop$Population
cyprus$percentage = (cyprus$people_vaccinated/cyprus$population)*100
plot_cyprus <- cyprus %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇨🇾") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_cyprus_1 = plot_cyprus+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_cyprus_1 = plot_cyprus_1 + ggtitle("Population Vaccinated \n on Cyprus (2021)") +
theme(plot.title = element_text(size = 6, face = "bold"))
plot_cyprus_percentage <- cyprus %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇨🇾") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_cyprus_2 = plot_cyprus_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_cyprus_2 = plot_cyprus_2 + ggtitle("Population (%) Vaccinated on Cyprus") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_cyprus_interactive <- plot_ly(x = cyprus$date, y = cyprus$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_cyprus_interactive2 <- plot_ly(x = cyprus$date, y = cyprus$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_cyprus_interactive3 <- plot_ly(x = cyprus$date, y = cyprus$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_cyprus_interactive,plot_cyprus_interactive2,plot_cyprus_interactive3, nrows=1)
Czech Republic - CZ
czech_rep <- vaccinations[grep("CZE", vaccinations$iso_code),]
czech_rep_world_pop <- world_population[grep("Czech", world_population$Country),]
czech_rep$population = czech_rep_world_pop$Population
czech_rep$percentage = (czech_rep$people_vaccinated/czech_rep$population)*100
plot_czech_rep <- czech_rep %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇨🇿") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_czech_rep_1 = plot_czech_rep+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_czech_rep_1 = plot_czech_rep_1 + ggtitle("Population Vaccinated \n on Czech Rep. (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_czech_rep_percentage <- czech_rep %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇨🇿") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_czech_rep_2 = plot_czech_rep_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_czech_rep_2 = plot_czech_rep_2 + ggtitle("Population (%) Vaccinated \n on Czech Rep.") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_czech_rep_interactive <- plot_ly(x = czech_rep$date, y = czech_rep$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_czech_rep_interactive2 <- plot_ly(x = czech_rep$date, y = czech_rep$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_czech_rep_interactive3 <- plot_ly(x = czech_rep$date, y = czech_rep$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_czech_rep_interactive,plot_czech_rep_interactive2,plot_czech_rep_interactive3, nrows=1)
Denmark - DK
denmark <- vaccinations[grep("DNK", vaccinations$iso_code),]
denmark_world_pop <- world_population[grep("Denmark", world_population$Country),]
denmark$population = denmark_world_pop$Population
denmark$percentage = (denmark$people_vaccinated/denmark$population)*100
plot_denmark <- denmark %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇩🇰") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_denmark_1 = plot_denmark+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_denmark_1 = plot_denmark_1 + ggtitle("Population Vaccinated on Denmark (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_denmark_percentage <- denmark %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇩🇰") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_denmark_2 = plot_denmark_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_denmark_2 = plot_denmark_2 + ggtitle("Population (%) Vaccinated \n on Denmark") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_denmark_interactive <- plot_ly(x = denmark$date, y = denmark$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_denmark_interactive2 <- plot_ly(x = denmark$date, y = denmark$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_denmark_interactive3 <- plot_ly(x = denmark$date, y = denmark$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_denmark_interactive,plot_denmark_interactive2,plot_denmark_interactive3, nrows=1)
Estonia - EE
estonia <- vaccinations[grep("EST", vaccinations$iso_code),]
estonia_world_pop <- world_population[grep("Estonia", world_population$Country),]
estonia$population = estonia_world_pop$Population
estonia$percentage = (estonia$people_vaccinated/estonia$population)*100
plot_estonia <- estonia %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇪🇪") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_estonia_1 = plot_estonia+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_estonia_1 = plot_estonia_1 + ggtitle("Population Vaccinated \n on Estonia (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_estonia_percentage <- estonia %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇪🇪") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_estonia_2 = plot_estonia_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_estonia_2 = plot_estonia_2 + ggtitle("Population (%) Vaccinated \n on Estonia") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_estonia_interactive <- plot_ly(x = estonia$date, y = estonia$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_estonia_interactive2 <- plot_ly(x = estonia$date, y = estonia$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_estonia_interactive3 <- plot_ly(x = estonia$date, y = estonia$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_estonia_interactive,plot_estonia_interactive2,plot_estonia_interactive3, nrows=1)
Finland - FI
finland <- vaccinations[grep("FIN", vaccinations$iso_code),]
finland_world_pop <- world_population[grep("Finland", world_population$Country),]
finland$population = finland_world_pop$Population
finland$percentage = (finland$people_vaccinated/finland$population)*100
plot_finland <- finland %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇫🇮") +
scale_y_continuous(breaks = seq(0, 100, 20),limits = c(0, 100))+
theme_wsj()
plot_finland_1 = plot_finland+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_finland_1 = plot_finland_1 + ggtitle("Population (%) Vaccinated \n on Finland (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_finland_percentage <- finland %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇫🇮") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_finland_2 = plot_finland_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_finland_2 = plot_finland_2 + ggtitle("Population (%) Vaccinated\n on Finland") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_finland_interactive <- plot_ly(x = finland$date, y = finland$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_finland_interactive2 <- plot_ly(x = finland$date, y = finland$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_finland_interactive3 <- plot_ly(x = finland$date, y = finland$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_finland_interactive,plot_finland_interactive2,plot_finland_interactive3, nrows=1)
France - FR
france <- vaccinations[grep("FRA", vaccinations$iso_code),]
france_world_pop <- world_population[grep("France", world_population$Country),]
france$population = france_world_pop$Population
france$percentage = (france$people_vaccinated/france$population)*100
plot_france <- france %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇫🇷") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_france_1 = plot_france+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_france_1 = plot_france_1 + ggtitle("Population Vaccinated \n on France (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_france_percentage <- france %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇫🇷") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_france_2 = plot_france_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_france_2 = plot_france_2 + ggtitle("Population (%) Vaccinated \n on France") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_france_interactive <- plot_ly(x = france$date, y = france$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_france_interactive2 <- plot_ly(x = france$date, y = france$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_france_interactive3 <- plot_ly(x = france$date, y = france$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_france_interactive,plot_france_interactive2,plot_france_interactive3, nrows=1)
Germany - DE
germany <- vaccinations[grep("DEU", vaccinations$iso_code),]
germany_world_pop <- world_population[grep("Germany", world_population$Country),]
germany$population = germany_world_pop$Population
germany$percentage = (germany$people_vaccinated/germany$population)*100
plot_germany <- germany %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇩🇪") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_germany_1 = plot_germany+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_germany_1 = plot_germany_1 + ggtitle("Population Vaccinated \n on Germany (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_germany_percentage <- germany %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇩🇪") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_germany_2 = plot_germany_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_germany_2 = plot_germany_2 + ggtitle("Population (%) Vaccinated \n on Germany") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_germany_interactive <- plot_ly(x = germany$date, y = germany$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_germany_interactive2 <- plot_ly(x = germany$date, y = germany$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_germany_interactive3 <- plot_ly(x = germany$date, y = germany$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_germany_interactive,plot_germany_interactive2,plot_germany_interactive3, nrows=1)
Gibraltar - GI
gibraltar <- vaccinations[grep("GIB", vaccinations$iso_code),]
gibraltar_world_pop <- world_population[grep("Gibraltar", world_population$Country),]
gibraltar$population = gibraltar_world_pop$Population
gibraltar$percentage = (gibraltar$people_vaccinated/gibraltar$population)*100
plot_gibraltar <- gibraltar %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇬🇮") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_gibraltar_1 = plot_gibraltar+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_gibraltar_1 = plot_gibraltar_1 + ggtitle("Population Vaccinated on Gibraltar (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_gibraltar_percentage <- gibraltar %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇬🇮") +
scale_y_continuous(breaks = seq(0, 40, 10),limits = c(0, 40))+
theme_wsj()
plot_gibraltar_2 = plot_gibraltar_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_gibraltar_2 = plot_gibraltar_2 + ggtitle("Population (%) Vaccinated \n on Gibraltar") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_gibraltar_interactive <- plot_ly(x = gibraltar$date, y = gibraltar$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_gibraltar_interactive2 <- plot_ly(x = gibraltar$date, y = gibraltar$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_gibraltar_interactive3 <- plot_ly(x = gibraltar$date, y = gibraltar$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_gibraltar_interactive,plot_gibraltar_interactive2,plot_gibraltar_interactive3, nrows=1)
Greece - GR
greece <- vaccinations[grep("GRC", vaccinations$iso_code),]
greece_world_pop <- world_population[grep("Greece", world_population$Country),]
greece$population = greece_world_pop$Population
greece$percentage = (greece$people_vaccinated/greece$population)*100
plot_greece <- greece %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇬🇷") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_greece_1 = plot_greece+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_greece_1 = plot_greece_1 + ggtitle("Population Vaccinated \n on Greece (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_greece_percentage <- greece %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇬🇷") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_greece_2 = plot_greece_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_greece_2 = plot_greece_2 + ggtitle("Population (%) Vaccinated \n on Greece") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_greece_interactive <- plot_ly(x = greece$date, y = greece$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_greece_interactive2 <- plot_ly(x = greece$date, y = greece$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_greece_interactive3 <- plot_ly(x = greece$date, y = greece$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_greece_interactive,plot_greece_interactive2,plot_greece_interactive3, nrows=1)
Hungary - HU
hungary <- vaccinations[grep("HUN", vaccinations$iso_code),]
hungary_world_pop <- world_population[grep("Hungary", world_population$Country),]
hungary$population = hungary_world_pop$Population
hungary$percentage = (hungary$people_vaccinated/hungary$population)*100
plot_hungary <- hungary %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("ðŸ‡ðŸ‡º") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_hungary_1 = plot_hungary + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_hungary_1 = plot_hungary_1 + ggtitle("Population (%) Vaccinated \n on Hungary (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_hungary_percentage <- hungary %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("ðŸ‡ðŸ‡º") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_hungary_2 = plot_hungary_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_hungary_2 = plot_hungary_2 + ggtitle("Population (%) Vaccinated \n on Hungary") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_hungary_interactive <- plot_ly(x = hungary$date, y = hungary$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_hungary_interactive2 <- plot_ly(x = hungary$date, y = hungary$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_hungary_interactive3 <- plot_ly(x = hungary$date, y = hungary$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_hungary_interactive,plot_hungary_interactive2, plot_hungary_interactive3,nrows=1)
Iceland - IS
iceland <- vaccinations[grep("ISL", vaccinations$iso_code),]
iceland_world_pop <- world_population[grep("Iceland", world_population$Country),]
iceland$population = iceland_world_pop$Population
iceland$percentage = (iceland$people_vaccinated/iceland$population)*100
plot_iceland <- iceland %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇮🇸") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_iceland_1 = plot_iceland + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_iceland_1 = plot_iceland_1 + ggtitle("Population Vaccinated on Iceland (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_iceland_percentage <- iceland %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇮🇸") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_iceland_2 = plot_iceland_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_iceland_2 = plot_iceland_2 + ggtitle("Population (%) Vaccinated \n on Iceland") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_iceland_interactive <- plot_ly(x = iceland$date, y = iceland$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_iceland_interactive2 <- plot_ly(x = iceland$date, y = iceland$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_iceland_interactive3 <- plot_ly(x = iceland$date, y = iceland$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_iceland_interactive,plot_iceland_interactive2,plot_iceland_interactive3 ,nrows=1)
India - IN
india <- vaccinations[grep("IND", vaccinations$iso_code),]
india_world_pop <- world_population[grep("India", world_population$Country),]
india$population = india_world_pop$Population
india$percentage = (india$people_vaccinated/india$population)*100
plot_india <- india %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇮🇳") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_india_1 = plot_india + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_india_1 = plot_india_1 + ggtitle("Population Vaccinated on India (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_india_percentage <- india %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇮🇳") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_india_2 = plot_india_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_india_2 = plot_india_2 + ggtitle("Population (%) Vaccinated \n on India (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_india_interactive <- plot_ly(x = india$date, y = india$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_india_interactive2 <- plot_ly(x = india$date, y = india$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_india_interactive3 <- plot_ly(x = india$date, y = india$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_india_interactive,plot_india_interactive2,plot_india_interactive3, nrows=1)
Indonesia - ID
indonesia <- vaccinations[grep("IDN", vaccinations$iso_code),]
indonesia_world_pop <- world_population[grep("Indonesia", world_population$Country),]
indonesia$population = indonesia_world_pop$Population
indonesia$percentage = (indonesia$people_vaccinated/indonesia$population)*100
plot_indonesia <- indonesia %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇮🇩") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_indonesia_1 = plot_indonesia + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_indonesia_1 = plot_indonesia_1 + ggtitle("Population Vaccinated on Indonesia (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_indonesia_percentage <- indonesia %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇮🇩") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_indonesia_2 = plot_indonesia_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_indonesia_2 = plot_indonesia_2 + ggtitle("Population (%) Vaccinated \n on Indonesia (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_indonesia_interactive <- plot_ly(x = indonesia$date, y = indonesia$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_indonesia_interactive2 <- plot_ly(x = indonesia$date, y = indonesia$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_indonesia_interactive3 <- plot_ly(x = indonesia$date, y = indonesia$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_indonesia_interactive,plot_indonesia_interactive2,plot_indonesia_interactive3, nrows=1)
NA
Ireland - IE
ireland <- vaccinations[grep("IRL", vaccinations$iso_code),]
ireland_world_pop <- world_population[grep("Ireland", world_population$Country),]
ireland$population = ireland_world_pop$Population
ireland$percentage = (ireland$people_vaccinated/ireland$population)*100
plot_ireland <- ireland %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇮🇪") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_ireland_1 = plot_ireland + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_ireland_1 = plot_ireland_1 + ggtitle("Population Vaccinated \n on Ireland (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_ireland_percentage <- ireland %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇮🇪") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_ireland_2 = plot_ireland_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_ireland_2 = plot_ireland_2 + ggtitle("Population (%) Vaccinated \n on Ireland (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_ireland_interactive <- plot_ly(x = ireland$date, y = ireland$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_ireland_interactive2 <- plot_ly(x = ireland$date, y = ireland$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_ireland_interactive3 <- plot_ly(x = ireland$date, y = ireland$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_ireland_interactive,plot_ireland_interactive2,plot_ireland_interactive3, nrows=1)
Israel - IL
israel <- vaccinations[grep("ISR", vaccinations$iso_code),]
israel_world_pop <- world_population[grep("Israel", world_population$Country),]
israel$population = israel_world_pop$Population
israel$percentage = (israel$people_vaccinated/israel$population)*100
plot_israel <- israel %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇮🇱") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_israel_1 = plot_israel + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_israel_1 = plot_israel_1 + ggtitle("Population Vaccinated \n on Israel (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_israel_percentage <- israel %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇮🇱") +
scale_y_continuous(breaks = seq(0, 40, 5),limits = c(0, 40))+
theme_wsj()
plot_israel_2 = plot_israel_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_israel_2 = plot_israel_2 + ggtitle("Population (%) Vaccinated \n on Israel (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_israel_interactive <- plot_ly(x = israel$date, y = israel$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_israel_interactive2 <- plot_ly(x = israel$date, y = israel$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_israel_interactive3 <- plot_ly(x = israel$date, y = israel$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_israel_interactive,plot_israel_interactive2,plot_israel_interactive3, nrows=1)
Italy - IT
italy <- vaccinations[grep("ITA", vaccinations$iso_code),]
italy_world_pop <- world_population[grep("Italy", world_population$Country),]
italy$population = italy_world_pop$Population
italy$percentage = (italy$people_vaccinated/italy$population)*100
plot_italy <- italy %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇮🇹") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_italy_1 = plot_italy + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_italy_1 = plot_italy_1 + ggtitle("Population Vaccinated \n on Italy(2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_italy_percentage <- italy %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇮🇹") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_italy_2 = plot_italy_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_italy_2 = plot_italy_2 + ggtitle("Population (%) Vaccinated \n on Italy (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_italy_interactive <- plot_ly(x = italy$date, y = italy$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_italy_interactive2 <- plot_ly(x = italy$date, y = italy$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_italy_interactive3 <- plot_ly(x = italy$date, y = italy$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_italy_interactive,plot_italy_interactive2,plot_italy_interactive3, nrows=1)
Kuwait - KW
kuwait <- vaccinations[grep("KWT", vaccinations$iso_code),]
kuwait_world_pop <- world_population[grep("Kuwait", world_population$Country),]
kuwait$population = kuwait_world_pop$Population
kuwait$percentage = (kuwait$people_vaccinated/kuwait$population)*100
plot_kuwait <- kuwait %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇰🇼") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_kuwait_1 = plot_kuwait + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_kuwait_1 = plot_kuwait_1 + ggtitle("Population Vaccinated \n on Kuwait(2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_kuwait_percentage <- kuwait %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇰🇼") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_kuwait_2 = plot_kuwait_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_kuwait_2 = plot_kuwait_2 + ggtitle("Population (%) Vaccinated \n on Kuwait (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_kuwait_interactive <- plot_ly(x = kuwait$date, y = kuwait$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_kuwait_interactive2 <- plot_ly(x = kuwait$date, y = kuwait$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_kuwait_interactive3 <- plot_ly(x = kuwait$date, y = kuwait$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_kuwait_interactive,plot_kuwait_interactive2,plot_kuwait_interactive3, nrows=1)
Latvia - LV
latvia <- vaccinations[grep("LVA", vaccinations$iso_code),]
latvia_world_pop <- world_population[grep("Latvia", world_population$Country),]
latvia$population = latvia_world_pop$Population
latvia$percentage = (latvia$people_vaccinated/latvia$population)*100
plot_latvia <- latvia %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇱🇻") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_latvia_1 = plot_latvia + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_latvia_1 = plot_latvia_1 + ggtitle("Population Vaccinated \n on Italy (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_latvia_percentage <- latvia %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇱🇻") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_latvia_2 = plot_latvia_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_latvia_2 = plot_latvia_2 + ggtitle("Population (%) Vaccinated \n on Latvia ") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_latvia_interactive <- plot_ly(x = latvia$date, y = latvia$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_latvia_interactive2 <- plot_ly(x = latvia$date, y = latvia$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_latvia_interactive3 <- plot_ly(x = latvia$date, y = latvia$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_latvia_interactive,plot_latvia_interactive2,plot_latvia_interactive3, nrows=1)
Lithuania - LT
lithuania <- vaccinations[grep("LTU", vaccinations$iso_code),]
lithuania_world_pop <- world_population[grep("Lithuania", world_population$Country),]
lithuania$population = lithuania_world_pop$Population
lithuania$percentage = (lithuania$people_vaccinated/lithuania$population)*100
plot_lithuania <- lithuania %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇱🇹") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_lithuania_1 = plot_lithuania + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_lithuania_1 = plot_lithuania_1 + ggtitle("Population Vaccinated \n on Lithuania ") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_lithuania_percentage <- lithuania %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇱🇹") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_lithuania_2 = plot_lithuania_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_lithuania_2 = plot_lithuania_2 + ggtitle("Population (%) Vaccinated \n on Lithuania (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_lithuania_interactive <- plot_ly(x = lithuania$date, y = lithuania$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_lithuania_interactive2 <- plot_ly(x = lithuania$date, y = lithuania$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_lithuania_interactive3 <- plot_ly(x = lithuania$date, y = lithuania$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_lithuania_interactive,plot_lithuania_interactive2,plot_lithuania_interactive3, nrows=1)
Luxemberg - LU
luxembourg <- vaccinations[grep("LUX", vaccinations$iso_code),]
luxembourg_world_pop <- world_population[grep("Luxembourg", world_population$Country),]
luxembourg$population = luxembourg_world_pop$Population
luxembourg$percentage = (luxembourg$people_vaccinated/luxembourg$population)*100
plot_luxembourg <- luxembourg %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇱🇺") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_luxembourg_1 = plot_luxembourg + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_luxembourg_1 = plot_luxembourg_1 + ggtitle("Population Vaccinated \n on Luxembourg") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_luxembourg_percentage <- italy %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇱🇺") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_luxembourg_2 = plot_luxembourg_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_luxembourg_2 = plot_luxembourg_2 + ggtitle("Population (%) Vaccinated \n on Luxembourg") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_luxembourg_interactive <- plot_ly(x = luxembourg$date, y = luxembourg$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_luxembourg_interactive2 <- plot_ly(x = luxembourg$date, y = luxembourg$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_luxembourg_interactive3 <- plot_ly(x = luxembourg$date, y = luxembourg$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_luxembourg_interactive,plot_luxembourg_interactive2,plot_luxembourg_interactive3, nrows=1)
Malta - MT
malta <- vaccinations[grep("MLT", vaccinations$iso_code),]
malta_world_pop <- world_population[grep("Malta", world_population$Country),]
malta$population = malta_world_pop$Population
malta$percentage = (malta$people_vaccinated/malta$population)*100
plot_malta <- malta %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇲🇹") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_malta_1 = plot_malta + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_malta_1 = plot_malta_1 + ggtitle("Population Vaccinated \n on Malta (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_malta_percentage <- malta %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇲🇹") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_malta_2 = plot_malta_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_malta_2 = plot_malta_2 + ggtitle("Population (%) Vaccinated \n on Malta") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_malta_interactive <- plot_ly(x = malta$date, y = malta$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_malta_interactive2 <- plot_ly(x = malta$date, y = malta$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_malta_interactive3 <- plot_ly(x = malta$date, y = malta$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_malta_interactive,plot_malta_interactive2,plot_malta_interactive3, nrows=1)
Mexico - MX
mexico <- vaccinations[grep("MEX", vaccinations$iso_code),]
mexico_world_pop <- world_population[grep("Mexico", world_population$Country),]
mexico$population = mexico_world_pop$Population
mexico$percentage = (mexico$people_vaccinated/mexico$population)*100
plot_mexico <- mexico %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇲🇽") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_mexico_1 = plot_mexico + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_mexico_1 = plot_mexico_1 + ggtitle("Population Vaccinated \n on Mexico ") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_mexico_percentage <- mexico %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇲🇽") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_mexico_2 = plot_mexico_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_mexico_2 = plot_mexico_2 + ggtitle("Population (%) Vaccinated \n on Mexico (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_mexico_interactive <- plot_ly(x = mexico$date, y = mexico$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_mexico_interactive2 <- plot_ly(x = mexico$date, y = mexico$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_mexico_interactive3 <- plot_ly(x = mexico$date, y = mexico$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_mexico_interactive,plot_mexico_interactive2,plot_mexico_interactive3, nrows=1)
Norway - NO
norway <- vaccinations[grep("NOR", vaccinations$iso_code),]
norway_world_pop <- world_population[grep("Norway", world_population$Country),]
norway$population = norway_world_pop$Population
norway$percentage = (norway$people_vaccinated/norway$population)*100
plot_norway <- norway %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇳🇴") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_norway_1 = plot_norway + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_norway_1 = plot_norway_1 + ggtitle("Population Vaccinated \n on Norway (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_norway_percentage <- norway %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇳🇴") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_norway_2 = plot_norway_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_norway_2 = plot_norway_2 + ggtitle("Population (%) Vaccinated \n on Morway (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_norway_interactive <- plot_ly(x = norway$date, y = norway$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_norway_interactive2 <- plot_ly(x = norway$date, y = norway$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_norway_interactive3 <- plot_ly(x = norway$date, y = norway$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_norway_interactive,plot_norway_interactive2,plot_norway_interactive3, nrows=1)
Oman - OM
oman <- vaccinations[grep("OMN", vaccinations$iso_code),]
oman_world_pop <- world_population[grep("Oman", world_population$Country),]
oman$population = oman_world_pop$Population
oman$percentage = (oman$people_vaccinated/oman$population)*100
plot_oman <- oman %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇴🇲") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_oman_1 = plot_oman + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_oman_1 = plot_oman_1 + ggtitle("Population Vaccinated \n on Oman(2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_oman_percentage <- oman %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇴🇲") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_oman_2 = plot_oman_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_oman_2 = plot_oman_2 + ggtitle("Population (%) Vaccinated \n on Oman (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_oman_interactive <- plot_ly(x = oman$date, y = oman$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_oman_interactive2 <- plot_ly(x = oman$date, y = oman$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_oman_interactive3 <- plot_ly(x = oman$date, y = oman$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_oman_interactive,plot_oman_interactive2,plot_oman_interactive3, nrows=1)
Panama - PA
panama <- vaccinations[grep("PAN", vaccinations$iso_code),]
panama_world_pop <- world_population[grep("Panama", world_population$Country),]
panama$population = panama_world_pop$Population
panama$percentage = (panama$people_vaccinated/panama$population)*100
plot_panama <- panama %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇵🇦") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_panama_1 = plot_panama + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_panama_1 = plot_panama_1 + ggtitle("Population Vaccinated \n on Panama (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_panama_percentage <- panama %>%
ggplot( aes(x=date, y = percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇵🇦") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_panama_2 = plot_panama_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_panama_2 = plot_panama_2 + ggtitle("Population (%) Vaccinated \n on Panama (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_panama_interactive <- plot_ly(x = panama$date, y = panama$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_panama_interactive2 <- plot_ly(x = panama$date, y = panama$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_panama_interactive3 <- plot_ly(x = panama$date, y = panama$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_panama_interactive,plot_panama_interactive2,plot_panama_interactive3, nrows=1)
Poland - PL
poland <- vaccinations[grep("POL", vaccinations$iso_code),]
poland_world_pop <- world_population[grep("Poland", world_population$Country),]
poland$population = poland_world_pop$Population
poland$percentage = (poland$people_vaccinated/poland$population)*100
plot_poland <- poland %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇵🇱") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_poland_1 = plot_poland + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_poland_1 = plot_poland_1 + ggtitle("Population Vaccinated \n on Poland (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_poland_percentage <- poland %>%
ggplot( aes(x=date, y = percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇵🇱") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_poland_2 = plot_poland_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_poland_2 = plot_poland_2 + ggtitle("Population (%) Vaccinated \n on Poland (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_poland_interactive <- plot_ly(x = poland$date, y = poland$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_poland_interactive2 <- plot_ly(x = poland$date, y = poland$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_poland_interactive3 <- plot_ly(x = poland$date, y = poland$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_poland_interactive,plot_poland_interactive2,plot_poland_interactive3, nrows=1)
Portugal - PT
portugal <- vaccinations[grep("PRT", vaccinations$iso_code),]
portugal_world_pop <- world_population[grep("Portugal", world_population$Country),]
portugal$population = portugal_world_pop$Population
portugal$percentage = (portugal$people_vaccinated/portugal$population)*100
plot_portugal <- portugal %>%
ggplot( aes(x=date, y=people_vaccinated, group=1)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇵🇹") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_portugal_1 = plot_portugal + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_portugal_1 = plot_portugal_1 + ggtitle("Population Vaccinated \n on Portugal (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_portugal_percentage <- portugal %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇵🇹") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_portugal_2 = plot_portugal_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_portugal_2 = plot_portugal_2 + ggtitle("Population (%) Vaccinated \n on Portugal (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_portugal_interactive <- plot_ly(x = portugal$date, y = portugal$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_portugal_interactive2 <- plot_ly(x = portugal$date, y = portugal$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_portugal_interactive3 <- plot_ly(x = portugal$date, y = portugal$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_portugal_interactive,plot_portugal_interactive2,plot_portugal_interactive3, nrows=1)
Romania - RO
romania <- vaccinations[grep("ROU", vaccinations$iso_code),]
romania_world_pop <- world_population[grep("Romania", world_population$Country),]
romania$population = romania_world_pop$Population
romania$percentage = (romania$people_vaccinated/romania$population)*100
plot_romania <- romania %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇷🇴") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_romania_1 = plot_romania + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_romania_1 = plot_romania_1 + ggtitle("Vaccination on \n Romania(2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_romania_percentage <- romania %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇷🇴") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_romania_2 = plot_romania_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_romania_2 = plot_romania_2 + ggtitle("Vaccination on \n Romania") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_romania_interactive <- plot_ly(x = romania$date, y = romania$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_romania_interactive2 <- plot_ly(x = romania$date, y = romania$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_romania_interactive3 <- plot_ly(x = romania$date, y = romania$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_romania_interactive,plot_romania_interactive2,plot_romania_interactive3, nrows=1)
Russia - RU
russia <- vaccinations[grep("RUS", vaccinations$iso_code),]
russia_world_pop <- world_population[grep("Russia", world_population$Country),]
russia$population = russia_world_pop$Population
russia$percentage = (russia$people_vaccinated/russia$population)*100
plot_russia <- russia %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇷🇺") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_russia_1 = plot_russia + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_russia_1 = plot_russia_1 + ggtitle("Vaccination on \n Russia(2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_russia_percentage <- russia %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇷🇺") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_russia_2 = plot_russia_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_russia_2 = plot_russia_2 + ggtitle("Vaccination on \n Russia") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_russia_interactive <- plot_ly(x = russia$date, y = russia$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_russia_interactive2 <- plot_ly(x = russia$date, y = russia$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_russia_interactive3 <- plot_ly(x = russia$date, y = russia$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_russia_interactive,plot_russia_interactive2,plot_russia_interactive3, nrows=1)
Saudi Arabia - SA
saudi_arabia <- vaccinations[grep("SAU", vaccinations$iso_code),]
saudi_arabia_world_pop <- world_population[grep("Saudi Arabia", world_population$Country),]
saudi_arabia$population = saudi_arabia_world_pop$Population
saudi_arabia$percentage = (saudi_arabia$people_vaccinated/saudi_arabia$population)*100
plot_saudi_arabia <- saudi_arabia %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇸🇦") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_saudi_arabia_1 = plot_saudi_arabia + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_saudi_arabia_1 = plot_saudi_arabia_1 + ggtitle("Vaccination on \n Saudi Arabia (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_saudi_arabia_percentage <- saudi_arabia %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇸🇦") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_saudi_arabia_2 = plot_saudi_arabia_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_saudi_arabia_2 = plot_saudi_arabia_2 + ggtitle("Vaccination on \n Saudi Arabia (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_saudi_arabia_interactive <- plot_ly(x = saudi_arabia$date, y = saudi_arabia$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_saudi_arabia_interactive2 <- plot_ly(x = saudi_arabia$date, y = saudi_arabia$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_saudi_arabia_interactive3 <- plot_ly(x = saudi_arabia$date, y = saudi_arabia$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_saudi_arabia_interactive,plot_saudi_arabia_interactive2,plot_saudi_arabia_interactive3, nrows=1)
Serbia - RS
serbia <- vaccinations[grep("SRB", vaccinations$iso_code),]
serbia_world_pop <- world_population[grep("Serbia", world_population$Country),]
serbia$population = serbia_world_pop$Population
serbia$percentage = (serbia$people_vaccinated/serbia$population)*100
plot_serbia <- serbia %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇷🇸") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_serbia_1 = plot_serbia + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_serbia_1 = plot_serbia_1 + ggtitle("Vaccination on \n Serbia (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_serbia_percentage <- serbia %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇷🇸") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_serbia_2 = plot_serbia_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_serbia_2 = plot_serbia_2 + ggtitle("Vaccination on \n Serbia (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_serbia_interactive <- plot_ly(x = serbia$date, y = serbia$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_serbia_interactive2 <- plot_ly(x = serbia$date, y = serbia$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_serbia_interactive3 <- plot_ly(x = serbia$date, y = serbia$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_serbia_interactive,plot_serbia_interactive2,plot_serbia_interactive3, nrows=1)
Seychelles - SC
seychelles <- vaccinations[grep("SYC", vaccinations$iso_code),]
seychelles_world_pop <- world_population[grep("Seychelles", world_population$Country),]
seychelles$population = seychelles_world_pop$Population
seychelles$percentage = (seychelles$people_vaccinated/seychelles$population)*100
plot_seychelles <- seychelles %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇸🇨") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_seychelles_1 = plot_seychelles + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_seychelles_1 = plot_seychelles_1 + ggtitle("Vaccination on \n Seychelles (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_seychelles_percentage <- seychelles %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇸🇨") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_seychelles_2 = plot_seychelles_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_seychelles_2 = plot_seychelles_2 + ggtitle("Vaccination on \n Seychelles (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_seychelles_interactive <- plot_ly(x = seychelles$date, y = seychelles$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_seychelles_interactive2 <- plot_ly(x = seychelles$date, y = seychelles$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_seychelles_interactive3 <- plot_ly(x = seychelles$date, y = seychelles$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_seychelles_interactive,plot_seychelles_interactive2,plot_seychelles_interactive3, nrows=1)
Slovakia - SK
slovakia <- vaccinations[grep("SVK", vaccinations$iso_code),]
slovakia_world_pop <- world_population[grep("Slovakia", world_population$Country),]
slovakia$population = slovakia_world_pop$Population
slovakia$percentage = (slovakia$people_vaccinated/slovakia$population)*100
plot_slovakia <- slovakia %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇸🇰") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_slovakia_1 = plot_slovakia + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_slovakia_1 = plot_slovakia_1 + ggtitle("Vaccination on \n Slovakia (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_slovakia_percentage <- slovakia %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇸🇰") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_slovakia_2 = plot_slovakia_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_slovakia_2 = plot_slovakia_2 + ggtitle("Vaccination on \n Slovakia (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_slovakia_interactive <- plot_ly(x = slovakia$date, y = slovakia$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_slovakia_interactive2 <- plot_ly(x = slovakia$date, y = slovakia$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_slovakia_interactive3 <- plot_ly(x = slovakia$date, y = slovakia$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_slovakia_interactive,plot_slovakia_interactive2,plot_slovakia_interactive3 , nrows=1)
Slovenia - SI
slovenia <- vaccinations[grep("SVN", vaccinations$iso_code),]
slovenia_world_pop <- world_population[grep("Slovenia", world_population$Country),]
slovenia$population = slovenia_world_pop$Population
slovenia$percentage = (slovenia$people_vaccinated/slovenia$population)*100
plot_slovenia <- slovenia %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇸🇮") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_slovenia_1 = plot_slovenia + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_slovenia_1 = plot_slovenia_1 + ggtitle("Vaccination on \n Slovenia (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_slovenia_percentage <- slovenia %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇸🇮") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_slovenia_2 = plot_slovenia_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_slovenia_2 = plot_slovenia_2 + ggtitle("Vaccination on \n Slovenia (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_slovenia_interactive <- plot_ly(x = slovenia$date, y = slovenia$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_slovenia_interactive2 <- plot_ly(x = slovenia$date, y = slovenia$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_slovenia_interactive3 <- plot_ly(x = slovenia$date, y = slovenia$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_slovenia_interactive,plot_slovenia_interactive2,plot_slovenia_interactive3, nrows=1)
Spain - ES
spain <- vaccinations[grep("ESP", vaccinations$iso_code),]
spain_world_pop <- world_population[grep("Spain", world_population$Country),]
spain$population = spain_world_pop$Population
spain$percentage = (spain$people_vaccinated/spain$population)*100
plot_spain <- spain %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇪🇸") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_spain_1 = plot_spain + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_spain_1 = plot_spain_1 + ggtitle("Vaccination on \n Spain (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_spain_percentage <- spain %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇪🇸") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_spain_2 = plot_spain_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_spain_2 = plot_spain_2 + ggtitle("Vaccination on \n Spain (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_spain_interactive <- plot_ly(x = spain$date, y = spain$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_spain_interactive2 <- plot_ly(x = spain$date, y = spain$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_spain_interactive3 <- plot_ly(x = spain$date, y = spain$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_spain_interactive,plot_spain_interactive2,plot_spain_interactive3, nrows=1)
Sweden - SE
sweden <- vaccinations[grep("SWE", vaccinations$iso_code),]
sweden_world_pop <- world_population[grep("Sweden", world_population$Country),]
sweden$population = sweden_world_pop$Population
sweden$percentage = (sweden$people_vaccinated/sweden$population)*100
plot_sweden <- sweden %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇸🇪") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_sweden_1 = plot_sweden + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
Turkey - TR
turkey <- vaccinations[grep("TUR", vaccinations$iso_code),]
turkey_world_pop <- world_population[grep("Turkey", world_population$Country),]
turkey$population = turkey_world_pop$Population
turkey$percentage = (turkey$people_vaccinated/turkey$population)*100
plot_turkey <- turkey %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇹🇷") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_turkey_1 = plot_turkey + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_turkey_1 = plot_turkey_1 + ggtitle("Vaccination on \n Turkey (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_turkey_percentage <- turkey %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇹🇷") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_turkey_2 = plot_turkey_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_turkey_2 = plot_turkey_2 + ggtitle("Vaccination on \n Turkey (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_turkey_interactive <- plot_ly(x = turkey$date, y = turkey$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_turkey_interactive2 <- plot_ly(x = turkey$date, y = turkey$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_turkey_interactive3 <- plot_ly(x = turkey$date, y = turkey$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_turkey_interactive,plot_turkey_interactive2,plot_turkey_interactive3, nrows=1)
United Arab Emirates - AE
uae <- vaccinations[grep("ARE", vaccinations$iso_code),]
uae_world_pop <- world_population[grep("United Arab Emirates", world_population$Country),]
uae$population = uae_world_pop$Population
uae$percentage = (uae$people_vaccinated/uae$population)*100
plot_uae <- uae %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇦🇪") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_uae_1 = plot_uae + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_uae_1 = plot_uae_1 + ggtitle("Vaccination on \n UAE (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_uae_percentage <- uae %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇦🇪") +
scale_y_continuous(breaks = seq(0, 40, 5),limits = c(0, 40))+
theme_wsj()
plot_uae_2 = plot_uae_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_uae_2 = plot_uae_2 + ggtitle("Vaccination on \n UAE (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_uae_interactive <- plot_ly(x = uae$date, y = uae$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_uae_interactive2 <- plot_ly(x = uae$date, y = uae$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_uae_interactive3 <- plot_ly(x = uae$date, y = uae$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_uae_interactive,plot_uae_interactive2,plot_uae_interactive3, nrows=1)
United Kingdom - UK
uk <- vaccinations[grep("GBR", vaccinations$iso_code),]
uk_world_pop <- world_population[grep("United Kingdom", world_population$Country),]
uk$population = uk_world_pop$Population
uk$percentage = (uk$people_vaccinated/uk$population)*100
plot_uk <- uk %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇬🇧") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_uk_1 = plot_uk + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_uk_1 = plot_uk_1 + ggtitle("Vaccination on \n United Kingdom (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_uk_percentage <- uk %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇬🇧") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_uk_2 = plot_uk_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_uk_2 = plot_uk_2 + ggtitle("Vaccination on \n UK (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_uk_interactive <- plot_ly(x = uk$date, y = uk$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_uk_interactive2 <- plot_ly(x = uk$date, y = uk$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_uk_interactive3 <- plot_ly(x = uk$date, y = uk$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_uk_interactive,plot_uk_interactive2,plot_uk_interactive3 , nrows=1)
United States of America - US
usa <- vaccinations[grep("USA", vaccinations$iso_code),]
usa_world_pop <- world_population[grep("United States", world_population$Country),]
usa$population = usa_world_pop$Population
usa$percentage = (usa$people_vaccinated/usa$population)*100
plot_usa <- usa %>%
ggplot( aes(x=date, y=people_vaccinated)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇺🇸") +
scale_y_continuous(breaks = seq(0, 10000000, 2000000),limits = c(0, 10000000))+
theme_wsj()
plot_usa_1 = plot_usa + theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_usa_1 = plot_usa_1 + ggtitle("Vaccination on \n USA (2021)") +
theme(plot.title = element_text(size = 10, face = "bold"))
plot_usa_percentage <- usa %>%
ggplot( aes(x=date, y=percentage)) +
geom_point()+
geom_line(color="#69b3a2") +
xlab("🇺🇸") +
scale_y_continuous(breaks = seq(0, 20, 2),limits = c(0, 20))+
theme_wsj()
plot_usa_2 = plot_usa_percentage+ theme(axis.text.x = element_text(face="bold", color="#993333",
size=7, angle=45))
plot_usa_2 = plot_usa_2 + ggtitle("Vaccination on \n USA (2021)") +
theme(plot.title = element_text(size = 7, face = "bold"))
plot_usa_interactive <- plot_ly(x = usa$date, y = usa$people_vaccinated, type="scatter", mode="markers", fill = "tozeroy")
plot_usa_interactive2 <- plot_ly(x = usa$date, y = usa$percentage, type="scatter", mode="markers", fill = "tozeroy")
plot_usa_interactive3 <- plot_ly(x = usa$date, y = usa$daily_vaccinations, type="scatter", mode="markers", fill = "tozeroy")
plotly::subplot(plot_usa_interactive,plot_usa_interactive2,plot_usa_interactive3, nrows=1)